Cerebral palsy after neonatal encephalopathy: do neonates with suspected asphyxia have worse outcomes?
Bibliographic record
Abstract
AIM: We sought to investigate how brain injury and severity, and neurological subtype of cerebral palsy (CP) differed in term-born children with CP after neonatal encephalopathy, between those with suspected birth asphyxia and those without. METHOD: Using the Canadian CP Registry, which included 1001 children, those with CP born at ≥ 36 wks after moderate or severe neonatal encephalopathy, were dichotomized according to the presence or absence of suspected birth asphyxia. Gross Motor Function Classification System (GMFCS) scores, neurological subtypes, comorbidities, and magnetic resonance imaging findings were compared. RESULTS: Of the 147 term-born children with CP (82 males, 65 females; median age 37 months, interquartile range [IQR] 26-52.5) who after moderate or severe neonatal encephalopathy had the required outcome data, 61 (41%) met criteria for suspected birth asphyxia. They had a higher frequency of non-ambulatory GMFCS status (odds ratio [OR] 3.4, 95% confidence interval [CI] 1.72-6.8), spastic quadriplegia (OR 2.8, 95% CI 1.4-5.6), non-verbal communication skills impairment (OR 4.2, 95% CI 2.0-8.6), isolated deep grey matter injury (OR 4.1, 95% CI 1.8-9.5), a lower frequency of spastic hemiplegia (OR 0.17, 95% CI 0.07-0.42), focal injury (OR 0.20; 95% CI 0.04-0.93), and more comorbidities (p=0.017) than those who did not meet criteria. INTERPRETATION: Term-born children who develop CP after neonatal encephalopathy with suspected birth asphyxia have a greater burden of disability than those without suspected birth asphyxia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".